UCL Institute of Health Informatics


Vincent Nguyen

PhD Student

Institute of Health Informatics
Faculty of Population Health Sciences

Academic Bakground

BSc in Computer Science, UCL 

MSc in Health Informatics, UCL 

Research summary

My research focuses on "Using public health data sciences to improve measures of type II diabetes and developing analytical methods to better account for biases in evaluations of public health interventions".

Background: The NHS Health Check and Diabetes Prevention Programme are expensive population-level interventions without strong trial-based evidence of effectiveness.  Observational studies are prone to problems such as missing data, confounding and selection biases. My PhD evaluates the effectiveness of the programmes and compare the influence of different analytical techniques to inform future design of observational studies.

Methods: Study design:  Two Retrospective Cohort studies assessing effectiveness of a) NHS Health Check and b) NHS Diabetes Prevention Programme on diabetes health outcomes. 

Target populations: those eligible for a) NHS Health Check (2009-16) and b) NHS Diabetes Prevention Programme (2016-2018) identified through demographic and READ code variables in Up to Standard Electronic Health Records

Intervention identification: Dedicated READ codes for the NHS Health Check and Diabetes Prevention Programme supplemented by previously established algorithms for the NHSHC.

Outcomes:  Incidence of Diabetes diagnosis, HbA1c, Chronic Kidney Disease, Retinopathy and Foot Complications up to 5 years following the health checks. 

Covariates include: Urinary Albumin levels, Framingham Score, and BMI.

Analytical approaches: Our primary approach is to use multiple imputation for missing data and propensity score matching (PSM) to ensure similarity of “treated” (i.e. those undergoing interventions within the programme) and “untreated” groups.  We will undertake a variety of classical and emerging epidemiological approaches to missing data, confounding and selection bias and compare predictive power of different approaches.


President of the UCL Catholic Society (Incumbent)